International Journal of Scientific Research and Engineering Development

The present study investigates how AI-driven customer analytics and personalised marketing influence customer experience, customer loyalty and purchase intention in digital markets, applying a Stimulus-Organism-Response framework extended with privacy concerns as a boundary condition. Data were drawn from a quantitative survey of respondents recruited through online panels; indicator reliability, convergent validity, discriminant validity and a series of nested regression models were estimated. Results show that AI-driven personalisation has a strong positive effect on customer experience (β = 0.492, p < .001) and that experience, in turn, is the strongest single predictor of purchase intention (β = 0.245, p < .001). Customer loyalty carries a substantial additional effect on purchase intention (β = 0.233, p < .001) and mediates approximately one fifth of the total CX→PI relationship. Privacy concerns exert a small but significant negative effect on purchase intention (β = −0.099, p < .05) without moderating the personalisation path (interaction β = 0.003, n.s.). The model explains 28.8 % of the variance in purchase intention. Findings suggest that the business value of AI-driven personalisation lies primarily in improving the customer experience, which then cascades into loyalty and purchase decisions. Theoretical, managerial and policy implications are discussed.

Shifa Bilal Tamboli, Simeen Phiroj Mulani, Arman Tajuddin Shiakh,"AI-Driven Customer Analytics and Personalized Marketing: Examining Customer Experience, Loyalty and Purchase Intention In Digital Markets" International Journal of Scientific Research and Engineering Development, V9(2): Page(3860-3866) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.